decisionnode/DecisionNode

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Latest release: v1.0.4
Disambiguation5/5
Each tool serves a distinct purpose: add/delete/get/update for individual decisions, list/search for retrieval, history for changelog, status for overview, and list_projects for context. No overlapping functionality.
Naming Consistency5/5
All tools follow a consistent verb_noun pattern in snake_case, e.g., add_decision, search_decisions, list_projects. No mixing of styles or ambiguous verbs.
Tool Count5/5
9 tools cover the decision management domain without excess or deficiency. Each tool earns its place, supporting CRUD, search, history, status, and project context.
Completeness5/5
The tool surface covers full lifecycle: creation, retrieval, update, deletion, listing, searching, history tracking, and status overview. No obvious gaps for typical decision management workflows.
Average 4.1/5 across 9 of 9 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- Last stable release on April 15, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
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```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It does not mention read-only nature, pagination, ordering, or limits. Given the lack of annotations, more detail is needed for transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two efficient sentences: the first states the action, the second adds usage context. No superfluous words, well front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has moderate complexity with 2 parameters and no output schema. The description lacks details on return value structure or pagination. Not fully complete for an agent to understand output expectations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the input schema already documents both parameters. The description does not add additional meaning beyond what the schema provides, achieving baseline 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'List all recorded decisions for the project' and provides context for when to use it (complete overview, starting new feature area), distinguishing it from siblings like get_decision (single) and search_decisions (search).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit use cases are given (complete overview, starting new feature), but no explicit exclusions or alternative tool names are mentioned. Implicitly, siblings like get_decision and search_decisions serve different purposes.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden for behavioral traits. It only states 'update' which implies mutation, but does not disclose any additional behaviors such as error handling, idempotency, access requirements, or side effects. This is insufficient for an update operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is only two sentences, front-loaded with the core purpose, and provides a concise usage guideline in the second sentence. Every word is necessary and there is no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 6 parameters (5 required), no annotations, and no output schema, the description is brief. It covers the basic use case but does not explain return values, error conditions, or partial updates. While adequate for a simple tool, it leaves some gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage with clear parameter descriptions. The description adds minimal value beyond the schema, stating the general purpose. Baseline of 3 is appropriate as the schema already provides adequate semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'update' and the resource 'existing decision', and explicitly differentiates from creating duplicate decisions. This provides a specific purpose that distinguishes it from siblings like add_decision.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says 'Use this instead of creating duplicate decisions', giving clear guidance on when to use. It also mentions the context of changing requirements or evolving approach. However, it does not explicitly list other alternatives or when not to use, though the sibling tools provide context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It discloses it's a read-only operation ('view'), but lacks details on output format, pagination, or auth requirements. Schema covers parameter descriptions, but behavioral context is minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with zero waste. First sentence states purpose, second adds usage context. Front-loaded and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no output schema and two required parameters, the description adequately covers purpose but misses details like return format, ordering, and that project is required for scoping. Adequate but not comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline 3 applies. The description adds no extra meaning beyond what the schema provides; it does not elaborate on how to use parameters effectively.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool reads the activity log of recent decision changes, distinguishing it from sibling tools like list_decisions (current state) or get_decision (single entry). The verb 'view' and resource 'activity log' are specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit instruction to use for understanding recent additions or modifications. No alternatives mentioned, but the context of siblings allows inference. Clear when-to-use, but no when-not-to.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that the tool returns a status overview with total count and last activity, indicating a read operation. However, it does not discuss any behavioral aspects like idempotency, side effects, or rate limits, which are less critical for a simple read but still missing.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description consists of two sentences, is completely front-loaded with the primary action and outputs, and contains no unnecessary words or information. Every sentence serves a clear purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, no output schema, no annotations), the description is largely complete: it states the purpose and the key outputs. It does not explain the output format or aggregation details, but those are likely covered by the sibling tools and the context of a quick health check.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage with a description for the 'project' parameter ('The workspace folder name'). The tool description does not add extra information beyond what the schema already provides, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool gets a project decision status overview including total count and last activity. The verb 'get' and resource 'project decision status overview' are specific, and it distinguishes itself from siblings like 'get_decision' (single decision) and 'list_decisions' (list without status overview).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says 'Use this for a quick health check of the decision store,' which provides clear context for when to use it. It does not mention when not to use or name alternatives, but the guidance is sufficient for a simple tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It implies a safe read operation and focuses on usage context. It does not disclose potential side effects, auth requirements, or rate limits, which is adequate but not exhaustive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with an example, front-loading the key instruction. No unnecessary words; every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple parameter set and no output schema, the description adequately covers usage and interpretation. Could be improved by describing the output format, but not essential for a listing tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% for a single boolean parameter with a clear description. The tool description does not add further meaning beyond the schema, so baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it lists all projects in monorepos/multi-project workspaces. The verb 'list' and resource 'projects' are specific, and it distinguishes from sibling tools (which are decision-focused) by indicating it should be called first.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says 'Call this FIRST if unsure which project to use,' providing clear context. It also gives guidance on matching project names to subfolders in the user's file path. Lacks explicit when-not-to-use or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility. It reveals important behavioral traits: call during conversation, focus on why, and that the 'force' parameter skips conflict detection. It does not mention mutability or idempotency but is transparent enough for a write operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a bold imperative opening, bulleted triggers, and behavioral notes. Every sentence adds value, though it is somewhat lengthy. It efficiently conveys crucial information without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (7 parameters, 5 required, no output schema), the description covers purpose and usage well but lacks details about return values or default behavior in conflict scenarios. It hints at conflict detection via 'force' but doesn't describe what happens normally, which is a gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has 100% description coverage, so baseline is 3. The description adds value by explaining the 'global' and 'force' parameters beyond the schema, clarifying their purpose and usage. This lifts the score above baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: capturing decisions when specific phrases are uttered or when design/architectural choices are made. It uses a specific verb ('capture decisions') and resource ('decisions'), and distinguishes itself from sibling tools like search_decisions or delete_decision.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly tells when to call the tool ('IMMEDIATELY' upon decision phrases) and provides extensive examples and triggers. However, it does not specify when not to use it or mention alternative tools for viewing decisions, though the sibling list provides context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It implies read-only behavior and mentions returning 'full details including rationale and constraints', but does not disclose authentication requirements, rate limits, or any side effects. Adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with no redundancy. The first sentence states the purpose, the second provides usage guidance. Every sentence is necessary.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description hints at return values ('full details including rationale and constraints'). The tool is simple with 2 params, so completeness is high, though missing error handling info.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Both 'id' and 'project' parameters have descriptions in the input schema (100% coverage). The description does not add additional parameter meaning beyond what's in the schema. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get full details of a specific decision by ID', using a specific verb and resource. It distinguishes itself from siblings like search_decisions by noting it provides 'complete context including rationale and constraints'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says 'Use this after search_decisions returns relevant results', providing clear context and naming the sibling tool to use before this one. This helps the agent understand the workflow.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses permanence ('Permanently delete'), but lacks details on side effects or authorization needs, though the context is sufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the action. Every sentence adds value, with no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema or annotations, the description provides necessary context: when to use, permanence, and alternative. Could mention immediate effect, but strong overall.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. Description does not add meaning beyond the schema's descriptions of 'Decision ID to delete' and 'The workspace folder name'.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Permanently delete a decision,' using a specific verb and resource. It differentiates from sibling tools like update_decision by providing usage conditions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use ('Only use when a decision was created in error') and when not to use ('For outdated decisions, prefer update_decision'), including a specific alternative.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations are not provided, so description carries full burden. It implies the tool is a safe read operation (searching) with no destructive behavior stated. Strongly indicates it's a required prerequisite step, but doesn't explicitly state it's read-only.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is front-loaded with the mandatory instruction. While verbose, every sentence is meaningful. Bold and caps for emphasis make it clear. Could be slightly shorter but maintains effectiveness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers when to call, what to query, and expected outcomes. Does not describe output structure (e.g., list of decisions with details), but usage guidance is comprehensive enough for agent to act correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and description adds value beyond schema: provides examples for query parameter, and gives explicit guidance for project parameter (REQUIRED, extract from path, call list_projects if unsure).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: search for existing decisions/conventions before making code changes. It uses the verb 'search' and resource 'decisions', and distinguishes itself from siblings like add_decision, delete_decision, etc. by emphasizing it must be called first.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says 'MANDATORY: Call this FIRST before ANY code changes.' Provides detailed when-to-use scenarios (add feature, modify code, fix bug, etc.) and what to query. Also explains what to do if no decisions exist (proceed freely) and if they exist (follow them).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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